Qi Meng
26 papers · 2016–2026 · 9 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
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Research topics
Machine Learning
(20)
Deep Learning
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Optimization & Theory Β· Machine Learning
(14)
Application Areas
(8)
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Core Methods
(5)
Models
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Reinforcement Learning
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neural network
(4)
graph neural network
(3)
generalization bound
(3)
large language model
(3)
neural network optimization
(3)
deep learning
(2)
relu neural network
(2)
data augmentation
(2)
decision tree
(2)
asynchronous stochastic gradient descent
(2)
gradient boosting
(2)
gradient descent
(2)
generative model
(2)
convergence analysis
(1)
semantic analysis
(1)
uncertainty quantification
(1)
neural machine translation
(1)
kl divergence
(1)
policy gradient
(1)
contrastive learning
(1)
Papers
MASFactory: A Graph-centric Framework for Orchestrating LLM-Based Multi-Agent Systems with Vibe Graphing
ACL 2026
MSRL: Scaling Generative Multimodal Reward Modeling via Multi-Stage Reinforcement Learning
CVPR 2026
Generate or Re-Weight? A Mutual-Guidance Method for Class-Imbalanced Graphs
IJCAI 2025
HR-Extreme: A High-Resolution Dataset for Extreme Weather Forecasting
ICLR 2025
TEACH: A Contrastive Knowledge Adaptive Distillation Framework for Classical Chinese Understanding
ACL 2025
MEFT: Memory-Efficient Fine-Tuning through Sparse Adapter
ACL 2024
O-GNN: incorporating ring priors into molecular modeling
ICLR 2023
Deep Latent Regularity Network for Modeling Stochastic Partial Differential Equations
AAAI 2023
NeuralStagger: Accelerating Physics-constrained Neural PDE Solver with Spatial-temporal Decomposition
ICML 2023
Does Momentum Change the Implicit Regularization on Separable Data?
NeurIPS 2022
PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Prior
ICLR 2022
SE(3) Equivariant Graph Neural Networks with Complete Local Frames
ICML 2022
Optimizing Information-theoretical Generalization Bound via Anisotropic Noise of SGLD
NeurIPS 2021
Path-BN: Towards effective batch normalization in the Path Space for ReLU networks
UAI 2021
R-Drop: Regularized Dropout for Neural Networks
NeurIPS 2021
The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks
ICML 2021
UniDrop: A Simple yet Effective Technique to Improve Transformer without Extra Cost
NAACL 2021
I4R: Promoting Deep Reinforcement Learning by the Indicator for Expressive Representations
IJCAI 2020
Reinforcement Learning with Dynamic Boltzmann Softmax Updates
IJCAI 2020
Capacity Control of ReLU Neural Networks by Basis-Path Norm
AAAI 2019
G-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space
ICLR 2019
Differential Equations for Modeling Asynchronous Algorithms
IJCAI 2018
Asynchronous Stochastic Gradient Descent with Delay Compensation
ICML 2017
LightGBM: A Highly Efficient Gradient Boosting Decision Tree
NeurIPS 2017
A Communication-Efficient Parallel Algorithm for Decision Tree
NeurIPS 2016
Asynchronous Accelerated Stochastic Gradient Descent
IJCAI 2016